What this category of data looks like
Core data for this category comes from ecological environment law enforcement detachments, monitoring stations, pollutant discharge units, and third-party testing institutions. Daily documents include on-site inspection records, sampling records, monitoring reports, order for correction decisions, and administrative penalty decisions. Data sources cover online monitoring platforms, automatic pollution source monitoring data, ecological environment law enforcement systems, and third-party test reports. The update frequency is daily. Most document structures contain fixed business fields. For example, monitoring reports include sampling points, pollutant concentrations, exceedance thresholds, and other fields. Some on-site records have attached sampling photos or handwritten annotations. Units for data fields mostly follow environmental monitoring standards such as mg/m³, mg/L, and similar units.
What constraints these characteristics impose on the "document parsing and chunking" step
Daily updated batch data requires the parsing process to be efficient and stable, to avoid delaying law enforcement business progress due to parsing delays. The mixed parsing needs for multiple document types require support for multiple formats including PDF, Word, and HTML, while also supporting embedded tables, scanned documents, and image attachments. Key information in law enforcement documents is highly correlated. For example, exceedance data and penalty basis must be retained in the same paragraph or adjacent chunks, to avoid losing associated logic after splitting. Additionally, document formats exported from different systems have non-standard differences. Flexible formatting rules must be adapted to ensure core fields are not missed or garbled.
How to set the configurations
These configurations apply to FastGPT v4.17.0
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the typical paragraph length of law enforcement documents, avoids splitting core related fields such as sampling points and exceedance values |
chunkSplitter | Split by title + paragraph | Matches the chapter structure of monitoring reports and administrative penalty decisions, retains title information to improve the accuracy of key content recall |
customPdfParse | Enabled | Supports extracting PDF embedded table text and scanned document OCR content, covering document types with images or tables such as on-site inspection records and sampling records |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Adapts to the parsing time of a single multi-page monitoring report, avoids interrupting complete data extraction due to timeout |
chunkSettingMode | Manual mode | Adjusts chunking rules separately for different document types, adapts to the differences between long paragraphs of administrative penalty decisions and short entries of sampling records |
Three common mistakes
- After uploading a PDF containing on-site sampling photos, the parsing result has no image-related text or OCR-extracted descriptive content. Cause: The image OCR function of
customPdfParseis not enabled, only plain text content is extracted, ignoring the sampling description information attached to the photos. - After uploading an HTML interface document generated by javadoc, the parsing result is empty or only contains a small amount of original tag text. Cause: Custom parsing rules are not configured to adapt to the nested tag structure of HTML, and the default parsing logic cannot identify the core business content of the interface description.
- When uploading multiple monitoring reports in batches, some documents fail to parse and return a timeout error. Cause: The value of
PARSE_FILE_TIMEOUT_SECONDSis set too low, which does not match the actual parsing time of large-volume multi-page monitoring reports.
How to confirm the configuration is correct
- Upload a typical monitoring report, check whether the parsing result includes core fields such as sampling points, pollutant concentrations, and exceedance judgments, adjust
chunkSizeso that fields are not split. - Upload a law enforcement document containing embedded tables, verify that after
customPdfParseis enabled, the table text is completely extracted without missing or garbled characters. - Upload a single large-volume on-site inspection record, confirm that the parsing process does not trigger a timeout, adjust
PARSE_FILE_TIMEOUT_SECONDSto a value suitable for the scenario. - Upload an HTML document in javadoc format, verify that the custom parsing rules take effect and extract the core business content of the interface description.
The values given are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.